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Intermediate

Understanding Pairs Trading: Concepts and Cointegration

A focused, from-first-principles course on pairs trading for quant analyst aspirants, prop trading applicants, and traders looking to systematize their approach. Covers market-neutral thinking, spread construction, the z-score as a trading signal, and the formal statistical test that separates a real pairs trade from a coincidence: cointegration, via stationarity, the Augmented Dickey-Fuller test, and the Engle-Granger two-step method. Ends with screening, sizing, and managing a real pair from entry to exit. Built entirely on real NSE and BSE data, with Python throughout.

Pairs TradingCointegrationStatistical Arbitrage BasicsMean ReversionZ-Score Trading Signals
MODULES
4
DURATION
~3.2 hrs
TRACK
Quantitative Finance

What You'll Master

How pairs trading isolates alpha from a relationship between two assets instead of a directional market call
How to build a spread between two stocks and turn it into a z-score trading signal
Why correlation is not cointegration, and why that distinction decides whether a pair actually mean-reverts
How to test for stationarity and cointegration using the Augmented Dickey-Fuller and Engle-Granger tests
How to screen for candidate pairs, size a market-neutral position, and set entry/exit rules
How to manage a live pair: stop-losses, structural breaks, and the costs that eat into returns
Access Level
LEARNER
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Everything included
Full Text Playbooks
Actionable Exercises
Mobile Reading Mode
Lifetime Updates

Curriculum Breakdown

Chapter 1: The Idea of Pairs Trading

4 Lessons
▶
What Is Pairs Trading? Betting on a Relationship, Not a Direction10 min read
Preview
▶
Why Two Stocks Move Together: Correlation, Sector Ties, and Common Risk Factors10 min read
▶
Long-Short Construction: Building a Market-Neutral Position10 min read
▶
Case Study: A Classic Pair on the NSE and Why It Made Sense11 min read

Chapter 2: The Spread and the Z-Score

4 Lessons
▶
Building the Spread: Price Ratios vs Regression-Based Hedge Ratios10 min read
▶
The Z-Score: Measuring How Stretched a Spread Really Is10 min read
▶
Setting Entry and Exit Thresholds From the Z-Score9 min read
▶
Case Study: Calculating a Spread and Z-Score for Two NSE Banking Stocks12 min read

Chapter 3: Cointegration — The Statistical Backbone

5 Lessons
▶
Correlation Is Not Cointegration: Why the Distinction Matters9 min read
▶
Stationarity Explained: Random Walks vs Mean-Reverting Series10 min read
▶
The Augmented Dickey-Fuller Test for Stationarity11 min read
▶
The Engle-Granger Two-Step Method for Testing Cointegration12 min read
▶
Case Study: Testing an NSE Pair for Cointegration in Python13 min read

Chapter 4: Screening, Trading, and Managing a Pair

5 Lessons
▶
Screening the Market for Cointegrated Pair Candidates10 min read
▶
Position Sizing and Hedge Ratios in Practice10 min read
▶
When a Pair Breaks Down: Stop-Losses and Structural Change10 min read
▶
Costs, Slippage, and Practical Constraints for Indian Traders10 min read
▶
Case Study: A Full Pairs Trade Walkthrough From Screening to Exit13 min read